PP12: Bayesian posterior packets + selective gating (1.1261 BPB)#1043
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okezue wants to merge 1 commit intoopenai:mainfrom
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PP12: Bayesian posterior packets + selective gating (1.1261 BPB)#1043okezue wants to merge 1 commit intoopenai:mainfrom
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PR openai#1043 found early TTT chunks achieve 1.109 BPB (below SOTA!) but accumulated SGD updates cause drift to 1.126 by late chunks. Fix: periodically reset model weights to the original checkpoint. This prevents catastrophic drift while preserving local adaptation. Implementation: - TTT_RESET_EVERY=N: reset weights every N chunks (0=disabled) - Resets both weights and optimizer momentum state - Uses in-place copy (no reallocation, parameter references preserved) H100 sweep now tests 11 configurations: 6 temperatures × sliding eval 5 TTT configs: A: SOTA baseline (lr=0.002, 3ep) B: PR openai#1039 (lr=0.0025, 4ep) C: 5 epochs (lr=0.002, 5ep) D: PR openai#1039 + reset/100 (anti-drift) E: PR openai#1039 + reset/50 (anti-drift) If early chunks consistently hit 1.109 and reset prevents drift, the mean across all chunks could drop from 1.119 toward 1.110-1.114. That's record territory. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Summary
Test plan